Fits a Von Mises kernel distribution describing a linear variable as a function of a circular predictor, and boostraps the null distribution in order to evaluate significance of radial variation in the linear variable.
fitlincirc(circdat, lindat, pCI = 0.95, reps = 1000, res = 512)
Numeric vector of radian data matched with
Numeric vector of linear data matched with
Single numeric value between 0 and 1 defining proportional confidence interval to return.
Integer number of bootstrap repetitions to perform.
Resolution of fitted distribution and null confidence interval - specifically a single integer number of points on the circular scale at which to record distributions.
lindat from the null expecation is assessed either visually
by the degree to which the fitted distribution departs from the null confidence
interval (use generic plot function), or quantitatively by column
fit in the resulting
An object of type
Xu, H., Nichols, K. & Schoenberg, F.P. (2011) Directional kernel regression for wind and fire data. Forest Science, 57, 343-352.
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#Example with reps limited to increase speed data(BCIspeed) i <- BCIspeed$species=="ocelot" sp <- log(BCIspeed$speed[i]) tm <- BCIspeed$time[i]*2*pi mod <- fitlincirc(tm, sp, reps=50) plot(mod, CircScale=24, xaxp=c(0,24,4), xlab="Time", ylab="log(speed m/s)") legend(8,-3, c("Fitted speed", "Null CI"), col=1:2, lty=1:2)
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